Crosby, A. H. | Search bioRxiv

bioRxiv2020

Assessing performance of pathogenicity predictors using clinically-relevant variant datasets

PurposePathogenicity predictors are an integral part of genomic variant interpretation but, despite their widespread usage, an independent validation of performance using a clinically-relevant dataset has not been undertaken. MethodsWe derive two validation datasets: an "open" dataset containing variants extracted from publicly-available databases, similar to those commonly applied in previous benchmarking exercises, and a "clinically-representative" dataset containing variants identified through research/diagnostic exome and diagnostic panel sequencing. Using these datasets, we evaluate the performance of three recently developed meta-predictors, REVEL, GAVIN and ClinPred, and compare their performance against two commonly used in silico tools, SIFT and PolyPhen-2. ResultsAlthough the newer meta-predictors outperform the older tools, the performance of all pathogenicity predictors is substantially lower in the clinically-representative dataset. Using our clinically-relevant dataset, REVEL performed best with an area under the ROC of 0.81. Using a concordance-based approach based on a consensus of multiple tools reduces the performance due to both discordance between tools and false concordance where tools make common misclassification. Analysis of tool feature usage may give an insight into the tool performance and misclassification. ConclusionOur results support the adoption of meta-predictors over traditional in silico tools, but do not support a consensus-based approach as recommended by current variant classification guidelines.

genomics↗

bioRxiv2018

Growth disrupting mutations in epigenetic regulatory molecules are associated with abnormalities of epigenetic aging

Germline mutations in fundamental epigenetic regulatory molecules including DNA methyltransferase 3A (DNMT3A) are commonly associated with growth disorders, whereas somatic mutations are often associated with malignancy. We profiled genome-wide DNA methylation patterns in DNMT3A c.2312G>A; p.(Arg771Gln) carriers in a large Amish sibship with Tatton-Brown-Rahman syndrome (TBRS), their mosaic father and 15 TBRS patients with distinct pathogenic de novo DNMT3A variants. This defined widespread DNA hypomethylation at specific genomic sites enriched at locations annotated to genes involved in morphogenesis, development, differentiation, and malignancy predisposition pathways. TBRS patients also displayed highly accelerated DNA methylation aging. Notably, these findings were most striking in a carrier of the AML associated driver mutation p.Arg882Cys. Our studies additionally defined phenotype related accelerated and decelerated epigenetic aging in two histone methyltransferase disorders; NSD1 Sotos syndrome overgrowth disorder and KMT2D Kabuki syndrome growth impairment. Together, our findings provide fundamentally new insights into aberrant epigenetic mechanisms, the role of epigenetic machinery maintenance and determinants of biological aging in these growth disorders.

genetics↗